metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-1_5
model-index:
- name: phi-1_5-finetuned-qlora-cluster-gsm8k
results: []
phi-1_5-finetuned-qlora-cluster-gsm8k
This model is a fine-tuned version of microsoft/phi-1_5 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1536
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0717 | 1.0 | 233 | 1.1424 |
| 0.9785 | 2.0 | 467 | 1.1173 |
| 0.9489 | 3.0 | 701 | 1.1147 |
| 0.9226 | 4.0 | 935 | 1.1216 |
| 0.8962 | 5.0 | 1168 | 1.1204 |
| 0.8611 | 6.0 | 1402 | 1.1294 |
| 0.8424 | 7.0 | 1636 | 1.1372 |
| 0.8275 | 8.0 | 1870 | 1.1493 |
| 0.8187 | 9.0 | 2103 | 1.1526 |
| 0.8183 | 9.97 | 2330 | 1.1536 |
Framework versions
- PEFT 0.11.1
- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1